In this dissertation, I explore public health questions related to the current status of measles and rubella incidence and immunity, and the control of measles and rubella infections. Great strides have been made in the reduction of measles and rubella infections via vaccination. However, measles remains a significant cause of morbidity (20 million annual cases) and mortality (115,000 annual deaths); and rubella infection, typically mild among childhood, among pregnant women can cause the birth of an infant with congenital rubella syndrome (CRS) (105,000 annual CRS cases).
I built on an existing age-structured mathematical model to evaluate important public health questions in the context of measles and rubella control efforts. Mathematical models are increasingly relied upon for vaccination program design because formally framing the core mechanisms associated with transmission dynamics is essential to capturing important and potentially devastating non-linear effects in the dynamics of these infections.
In chapter 1, I evaluated the potential of introducing rubella-containing vaccine in India to reduce the burden of CRS, and found that introduction of the rubella vaccine will likely result in cumulative decreases in CRS. However, the effect of rubella vaccine introduction on the transient annual incidence of CRS is highly sensitive to rubella’s basic reproductive number. We identified risk factors that can be used to highlight regions most at risk of transient increases in CRS burden post-rubella vaccine introduction.
In chapter 2, I explored the use of a nested serological survey within the fever-rash surveil- lance system in Madagascar to estimate measles population immunity. We found discrepancies between direct and indirect empirical estimates of population immunity by age. However, both estimates indicated that Madagascar is at risk of a large measles outbreak. We evaluated the potential of measles Supplementary Immunization Activities to reduce this risk.
In chapter 3, I analyzed the strengths and limitations of rubella IgG serological data to characterize rubella epidemiological parameters and CRS incidence. We laid out in detail the nuanced biases from analytic method and survey design, which can be used by public health officials to better interpret past serological survey estimates, and to design, implement, and interpret future serological surveys.